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姓名	蘇德澤(Dimas Pradana Putra)  查詢紙本館藏	畢業系所	遙測科技碩士學位學程
論文名稱	2015年至2022年西北太平洋颱風對浮游植物和海表溫度的動態反應 (Dynamic Responses of Phytoplankton and Sea Surface Temperature to Typhoons in the Northwest Pacific (2015-2022))
相關論文	★ 評估菲律賓珊瑚礁區域的海洋熱浪與海洋酸化現象 ★ 臺灣鄰近海域的海洋熱浪及海洋寒潮事件
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摘要(中)	颱風對沿海和海洋環境影響深遠，包括對海洋動力學、生物地球化學循環及海洋生態系統的影響。本研究使用2015至2022年間來自向日葵衛星感測器和哥白尼海洋服務的衛星數據及再分析數據，探討颱風對西北太平洋地區浮游植物動態和海表溫度的影響。研究發現，在颱風中心250公里範圍內，二級颱風過境後4至5天，葉綠素濃度顯著增加，作為浮游植物生物量的指標。與開放海域相比，沿海地區因陸地營養物輸入和沿岸湧升作用而有更高的基線葉綠素濃度和更強烈的浮游植物增長。海表溫度分析顯示，颱風來臨前海表溫度先升高，隨後因湧升和大量降雨導致的淡水流入而顯著下降，且海表溫度變化幅度隨風暴強度增強。空間分析揭示沿海與開放水域在葉綠素和海表溫度動態上的顯著差異。此外，本研究發現颱風引發的葉綠素異常與厄爾尼諾-南方振盪（ENSO）狀態間存在顯著相關，特別是在高強度颱風中，顯示ENSO對颱風強度和海洋營養物動態有調節作用。深度剖析進一步揭示了這種相關性的垂直分布模式，反映了直接由颱風驅動的混合作用與ENSO引起的大尺度海洋循環變化之間的互動，特別是營養物從深層到表層的重新分布。
摘要(英)	Typhoons exert profound impacts on coastal and marine environments through their influence on ocean dynamics, biogeochemical cycles, and marine ecosystems. This study investigates the effects of typhoons on phytoplankton dynamics and sea surface temperature (SST) in the North West Pacific region from 2015 to 2022 using satellite data from the Himawari sensor and the Copernicus Marine Service. Analysis of chlorophyll-a concentrations, a proxy for phytoplankton biomass, revealed pronounced increases within a 250 km radius of the typhoon center, peaking 4-5 days after category 2 storm passages. Coastal areas exhibited higher baseline chlorophyll-a levels and more intense phytoplankton blooms compared to open ocean regions due to terrestrial nutrient inputs and coastal upwelling processes. Examination of SST patterns showed an initial increase before typhoon arrival, followed by a significant drop caused by upwelling and freshwater flux from heavy rainfall. The magnitude of SST changes varied with storm intensity, with category 5 typhoons inducing the highest SST peaks and subsequent declines within 250-500 km diameters. The spatial analysis highlighted differences in chlorophyll-a and SST responses between coastal and open ocean regions, underscoring the need for tailored strategies to mitigate typhoon impacts. Furthermore, the study uncovered a significant relationship between typhoon-induced chlorophyll-a anomalies and the El Niño-Southern Oscillation (ENSO) state, with stronger positive correlations in higher typhoon categories, suggesting that ENSO modulates both typhoon intensity and oceanic nutrient dynamics. Depth-resolved analyses revealed distinct vertical patterns in this relationship, reflecting the interplay between direct typhoon-driven mixing and larger-scale ENSO-induced changes in ocean circulation, particularly in the redistribution of nutrients from deeper layers to the surface.
關鍵字(中)	★ 颱風 ★ 葉綠素	關鍵字(英)	★ Typhoon ★ Chlorophyll-a
論文目次	Chinese abstract ……………………………………………….……………………………… i English Abstract ………………………………………………...…………………………… ii Acknowledgments …………………………………………………..………………………. iii Table of Contents …………………………………………………….……………………… iv List of Figures ………………………………………………………………………….…..Vi List of Tables………………………………………………………………….…………..Viii Chapter I Introduction………………………………………………………………………….1 1-1 Background…………………………………………………………………………1 1-2 Literature Review ……………………………………………………………………3 Chapter II Study Area……………………………………………………………………….…5 Chapter III Data and Method………………………………………..…………………………8 3-1 Dataset…………………………………………………………………….………….8 3-1-1 International Best Track Archive for Climate Stewardship (IBTrACS)………..8 3-1-2 Himawari Satellite Dataset……………………………….…………………….9 3-1-3 Copernicus Ocean Dataset……………………………………………………11 3-1-4 ENSO Indices…………………………………………………………………12 3-2 Methodology………………………………………………………………………...12 3-2-1 Himawari SST and Chl-a Dataset Pre-Processing…………………….………13 3-2-2 ENSO Influence Analysis………………………………………………….…14 Chapter IV Result and Discussion…………………………………………………………....15 4-1 Result……………………………………………………………………………...15 4-1-1 Time Series Trends in Chl-a……………………………………………….….15 4-1-1-1 Chl-a from Himawari Level 3 Dataset……………………………..…..15 4-1-1-2 Chl-a from Copernicus Level 4 Dataset……………………….………20 4-1-2 Spatial Distribution of Chl-a………………………………………………….25 4-1-3 Time Series Trends in the SST Dataset………………………………………..31 4-1-3-1 SST from Himawari Level 3 Dataset…………………………………..31 4-1-3-2. SST from Copernicus Level 4 Dataset……………………….………..37 4-1-4 Spatial Distribution in SST Dataset…………………………………………39 4-1-5. Chl-a Distribution Variation in Two Bathymetry Areas……………….……..45 4-2 Discussion…………………………………………………………………………...52 4-2-1 Himawari Level 3 vs Copernicus Level 4 Dataset Comparison Discussion…..52 4-2-2 ENSO Influence…………………………………………………………….58 Chapter V Conclusion……………………………………………………………………….66 Bibliography…………………………………………………………………………….……68 Appendix……………………………………………………………………………………..86
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指導教授	許伯駿(Hsu Po-Chun)	審核日期	2024-7-11
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